A new composite index called the yearly tropical cyclone potential impact(YTCPI)is introduced.The relationship between YTCPI and activities of tropical cyclones(TCs)in China,disaster loss,and main ambient fields are investigated to show the potential of YTCPI as a new tool for short-term climate prediction of TCs.YTCPI can indicate TC activity and potential disaster loss.As correlation coefficients between YTCPI and frequency of landfalling TCs,the frequency of TCs traversing or forming inside a 24 h warning line in China from 1971 to 2010 are 0.58 and 0.56,respectively(both are at a statistically significant level,aboveα=0.001).Furthermore,three simple indexes are used to compare with YTCPI.They all have very close relationships with it,with correlation coefficients 0.75,0.82 and 0.78.For economic loss and YTCPI,the correlation coefficient is 0.57 for 1994–2009.Information on principal ambient fields(sea surface temperature,850 and 500 hPa geopotential heights)during the previous winter is reflected in the relationship with YTCPI.Spatial and temporal variabilities of ambient fields are extracted through empirical orthogonal function(EOF)analysis.Spatial distributions of correlation coefficient between YTCPI and ambient fields match the EOF main mode.Correlation coefficients between YTCPI and the EOF time array for the three ambient fields are 0.46,0.44 and 0.4,respectively,all statistically significant,aboveα=0.01.The YTCPI has the overall potential to be an improved prediction tool. 相似文献
Dissolved pollutants in stormwater are a main contributor to water pollution in urban environments. However, many existing transport models are semi-empirical and only consider one-dimensional flows, which limit their predictive capacity. Combining the shallow water and the advection–diffusion equations, a two-dimensional physically based model is developed for dissolved pollutant transport by adopting the concept of a ‘control layer’. A series of laboratory experiments has been conducted to validate the proposed model, taking into account the effects of buildings and intermittent rainfalls. The predictions are found to be in good agreement with experimental observations, which supports the assumption that the depth of the control layer is constant. Based on the validated model, a parametric study is conducted, focusing on the characteristics of the pollutant distribution and transport rate over the depth. The hyetograph, including the intensity, duration and intermittency, of rainfall event has a significant influence on the pollutant transport rates. The depth of the control layer, rainfall intensity, surface roughness and area length are dominant factors that affect the dissolved pollutant transport. Finally, several perspectives of the new pollutant transport model are discussed. This study contributes to an in-depth understanding of the dissolved pollutant transport processes on impermeable surfaces and urban stormwater management. 相似文献
Some limitations of the Hilbert–Huang transform (HHT) for nonlinear and nonstationary signal processing are remarked. As an enhancement to the HHT, a time varying vector autoregressive moving average (VARMA) model based method is proposed to calculate the instantaneous frequencies of the intrinsic mode functions (IMFs) obtained from the empirical mode decomposition (EMD) of a signal. By representing the IMFs as time varying VARMA model and using the Kalman filter to estimate the time varying model parameters, the instantaneous frequencies are calculated according to the time varying parameters, then the instantaneous frequencies and the envelopes derived from the cubic spline interpolation of the maxima of IMFs are used to yield the Hilbert spectrum. The analysis of the length of day dataset and the ground motion record El Centro (1940, N–S) shows that the proposed method offers advantages in frequency resolution, and produces more physically meaningful and readable Hilbert spectrum than the original HHT method, short-time Fourier transform (STFT) and wavelet transform (WT). The analysis of the seismic response of a building during the 1994 Northridge earthquake shows that the proposed method is a powerful tool for structural damage detection, which is expected as the promising area for future research. 相似文献